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A Square NAM Representation Method for Binary Images

机译：二值图像的平方Nam表示方法

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Jie He; Yunping Zheng; Hui Guo;
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年度 2016
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1. A NAM representation method for data compression of binary images [J] . Zheng Yunping, Chen Chuanbo, Sarem Mudar Tsinghua Science and Technology . 2009,第1期

机译：用于二进制图像数据压缩的NAM表示方法
2. A NAM Representation Method for Data Compression of Binary Images [J] . ZHENG Yunping, CHEN Chuanbo, Sarem Mudar 清华大学学报（英文版） . 2009,第001期

机译：用于二进制图像数据压缩的NAM表示方法
3. A novel binary image representation algorithm by using NAM and coordinate encoding procedure and its application to area calculation [J] . Yunping ZHENG, Mudar SAREM Frontiers of computer science in China . 2014,第5期

机译：基于NAM和坐标编码的二进制图像表示新算法及其在面积计算中的应用
4. A Square NAM Representation Method for Binary Images [C] . Jie He, Yunping Zheng, Hui Guo International Conference on Electrical Information and Mechatronics . 2012

机译：二进制图像的方形NAM表示方法
5. A boundary-based image segmentation and representation method for binary images. [D] . Nabors, David Hoy. 2000

机译：基于边界的二值图像分割与表示方法。
6. Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant moment digital representations [O] . Rajalakshmi Gurunathan, Bernard Van Emden, Sethuraman Panchanathan, 2004

机译：在早期果蝇胚胎图像中识别空间相似的基因表达模式：二元特征与不变矩数字表示
7. Figure 6: (A) Tree resulted the standard MP analysis of the 98-loci supermatrix of the Great Apes (Hominidae, Primates, Mammalia) constructed using the modified summary of Lehtonen et al. (2011) (see “Materials and Methods” for the details) and a posteriori rooted relatively Papio (length = 12,092, CI = 0.7877, RI = 0.5597); 34,022 characters are constant, and the number of the parsimony-informative characters is equal to 4,311. MP BS values are provided below branches. The only characters with non-ambiguous value of the outgroup (Papio) have been saved within concatenated alignment; (B) the average consensus tree of the score 0.00084 resulted the analysis of the Hennigian forest of the 5,507 trees derived from the binary representation of the 98-loci supermatrix of the Great Apes (Hominidae, Primates, Mammalia) (see “Materials and Methods” for the details); Papio is assumed to be the best all-plesiomorphic group. “Additional…” FORESTER’s output tree file (see “Materials and Methods” for the details) selected for future analyses; (C) the average consensus tree of the score 0.00090 resulted the analysis of the Hennigian forest of the 5,339 trees derived from the modified binary representation of the 98-loci supermatrix of the Great Apes (Hominidae, Primates, Mammalia) (see 6.I. and “Materials and Methods” for the details), but with all 168 trees, which contain the clade (Homo plus Pan) have been removed from the input forest. “Additional…” FORESTER’s output tree file (see “Materials and Methods”) selected for future analyses. [O] . -1

机译：图6：（A）树导致的标准MP分析的98-基因座的类人猿（人科，灵长类动物，哺乳动物），使用莱赫托宁等人的修改的摘要构成的超级矩阵。（2011）（参见细节“材料和方法”）以及相对植根狒狒后验概率（长度= 12092，CI = 0.7877，RI = 0.5597）; 34022个字符是恒定的，并且简约信息的字符数等于4311。下面提供分支MP BS值。与外类群（狒狒）的非模糊值的唯一的字符已被保存的级联对准内; （B）的得分0.00084的平均一致树导致从巨猿（原始人类，灵长类动物，哺乳动物）的98座超级矩阵的二进制表示获得的5507棵的Hennigian森林的分析（见“材料和方法”为细节）;狒狒被认为是最好的全祖征群。 “其他...” FORESTER的输出树文件（请参阅详细信息“材料和方法”），用于进一步的分析; （C）的分数0.00090的平均一致树导致从98个位点的类人猿（人科，灵长类动物，哺乳动物）的超级矩阵（见6.I的改性二进制表示导出的5339种树木的Hennigian森林的分析以及“材料和方法”的详细说明），但所有168棵，其中包含的分支（智人加PAN）已经从输入林中删除。 “其他...” FORESTER的输出树文件（参见“材料和方法”），用于进一步的分析。
8. Morphological Skeleton Representation and Coding of Binary Images [R] . Maragos, P. A., Schafer, R. W. 1984

机译：二值图像的形态学骨架表示与编码

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